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QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data.
Estaki, Mehrbod; Jiang, Lingjing; Bokulich, Nicholas A; McDonald, Daniel; González, Antonio; Kosciolek, Tomasz; Martino, Cameron; Zhu, Qiyun; Birmingham, Amanda; Vázquez-Baeza, Yoshiki; Dillon, Matthew R; Bolyen, Evan; Caporaso, J Gregory; Knight, Rob.
Afiliação
  • Estaki M; Department of Pediatrics, University of California San Diego, La Jolla, California.
  • Jiang L; Division of Biostatistics, University of California San Diego, La Jolla, California.
  • Bokulich NA; Center for Applied Microbiome Science, Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona.
  • McDonald D; Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona.
  • González A; Department of Pediatrics, University of California San Diego, La Jolla, California.
  • Kosciolek T; Department of Pediatrics, University of California San Diego, La Jolla, California.
  • Martino C; Department of Pediatrics, University of California San Diego, La Jolla, California.
  • Zhu Q; Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland.
  • Birmingham A; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, California.
  • Vázquez-Baeza Y; Center for Microbiome Innovation, University of California San Diego, La Jolla, California.
  • Dillon MR; Department of Pediatrics, University of California San Diego, La Jolla, California.
  • Bolyen E; Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, California.
  • Caporaso JG; Center for Microbiome Innovation, University of California San Diego, La Jolla, California.
  • Knight R; Jacobs School of Engineering, University of California San Diego, La Jolla, California.
Curr Protoc Bioinformatics ; 70(1): e100, 2020 06.
Article em En | MEDLINE | ID: mdl-32343490
ABSTRACT
QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses-e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https//qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https//forum.qiime2.org. © 2020 The Authors. Basic Protocol Using QIIME 2 with microbiome data Support Protocol Further microbiome analyses.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Bases de Dados como Assunto / Microbiota Idioma: En Revista: Curr Protoc Bioinformatics Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Bases de Dados como Assunto / Microbiota Idioma: En Revista: Curr Protoc Bioinformatics Ano de publicação: 2020 Tipo de documento: Article